code: def test_unstack_actions(self):
      num_envs = 5
      action_spec = self.action_spec
      rng = np.random.RandomState()
      batched_action = np.array(
          [
              array_spec.sample_bounded_spec(action_spec, rng)
              for _ in range(num_envs)
          ]
      )
  
      # Test that actions are correctly unstacked when just batched in np.array.
      unstacked_actions = batched_py_environment.unstack_actions(
          batched_action
      )
      for action in unstacked_actions:
          self.assertAllEqual(action_spec.shape, action.shape)
  
imports: from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  import collections
  import functools
  from absl.testing import parameterized
  import numpy
  import tensorflow
  from tf_agents.environments import batched_py_environment
  from tf_agents.environments import random_py_environment
  from tf_agents.specs import array_spec
  from tf_agents.trajectories import time_step
label_desc: Use image node_id 9 for calling the BatchedPyEnvironmentTest obj's underlying member method code with example usage: obj.test_unstack_actions() without return types